「based」の検索結果

Expert knowledge for Azure Lighthouse development including decision making, security, configuration, integrations & coding patterns, and deployment. Use when configuring Lighthouse delegations, AOBO/PIM access, Arc/Sentinel integrations, policies/remediation, or Marketplace offers, and other Azure Lighthouse related development tasks. Not for Azure Arc (use azure-arc), Azure Managed Applications (use azure-managed-applications), Azure Resource Manager (use azure-resource-manager), Azure Role-based access control (use azure-rbac).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Policy development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when authoring JSON policies, deploying via ARM/Bicep/Terraform, enforcing security baselines, automating with Gatekeeper, or running policy-as-code in CI/CD, and other Azure Policy related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Role-based access control (use azure-rbac), Azure Resource Manager (use azure-resource-manager), Azure Security (use azure-security).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Managed Applications development including limits & quotas, security, configuration, and deployment. Use when designing createUiDefinition UIs, JIT access, managed identities, StorageAccountSelector, or Bicep-based catalog publishing, and other Azure Managed Applications related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Resource Manager (use azure-resource-manager), Azure Lighthouse (use azure-lighthouse), Azure Partner Solutions (use azure-partner-solutions).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Microsoft Discovery development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Discovery shared sessions, Bookshelf indexes, secure RBAC/CMK setups, REST jobs, or Docker-based tools, and other Azure Microsoft Discovery related development tasks. Not for Azure Portal (use azure-portal), Azure Resource Graph (use azure-resource-graph), Azure Monitor (use azure-monitor), Azure Cost Management (use azure-cost-management).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, limits & quotas, configuration, and deployment. Use when tuning Docker-based Anomaly Detector, ACI or IoT Edge deployments, univariate/multivariate APIs, or service limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Bastion development including best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring Bastion for AKS private clusters, VM scale sets, Entra ID auth, hub/spoke VNets, or IP-based cross-VNet access, and other Azure Bastion related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager), Azure VPN Gateway (use azure-vpn-gateway), Azure Firewall (use azure-firewall).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Active Directory B2C development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building B2C user flows/custom policies, configuring IdPs/MFA, securing APIs, automating CI/CD, or monitoring with Sentinel, and other Azure Active Directory B2C related development tasks. Not for Azure Role-based access control (use azure-rbac), Azure Information Protection (use azure-information-protection), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel).

日本語の概要は準備中です。原文の説明を表示しています。

Keep README files current with project changes. Use when project structure changes, features added, or setup instructions modified. Suggests README updates based on code changes. Triggers on significant project changes, new features, dependency changes.

日本語の概要は準備中です。原文の説明を表示しています。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

日本語の概要は準備中です。原文の説明を表示しています。

Static config-correctness linter for this instance - catches the silent-failure class (unquoted schedules, duplicate keys, unconfigured skills, mode typos, broken requires/MCP refs) that no run-based health skill can see. Notifies only on problems.

日本語の概要は準備中です。原文の説明を表示しています。

Amazon Brand Analytics interpretation and strategic insights for Brand Registry owners. Decode Search Frequency Rank (SFR) data, analyze Market Basket patterns, interpret Item Comparison reports, and extract demographic insights to optimize product strategy and advertising spend. Works with Brand Analytics data from all Amazon marketplaces. Requires Brand Registry access. Use when: (1) analyzing Search Frequency Rank data for keyword opportunities, (2) interpreting Market Basket data for cross-sell and bundling, (3) understanding Item Comparison competitive positioning, (4) extracting customer demographic insights, (5) optimizing product portfolio based on customer behavior, (6) building data-driven advertising strategies.

日本語の概要は準備中です。原文の説明を表示しています。

User-facing entry point for the wp-rocket issue workflow. Invoke directly to start a delivery run from a GitHub issue number, URL, or raw description. Runs inline in your conversation context; spawns specialist agents (ticket-writer, grooming-agent, challenger, backend-agent, frontend-agent, release-agent, lead-reviewer, qa-engineer) as isolated sub-agents; invokes supporting skills (knowledge-graph, dod, docs, issue-workflow) inline. Routes based on structured JSON outputs from each agent, manages loop counters, handles escalations, and maintains a live HTML run log.

日本語の概要は準備中です。原文の説明を表示しています。

Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a name.

日本語の概要は準備中です。原文の説明を表示しています。

Build and execute brand marketing strategy for B2B companies — thought leadership, ABM brand layer, trust signals, LinkedIn presence, long sales cycle brand touchpoints, and enterprise credibility. Use when the user says "B2B marketing", "B2B brand", "business to business marketing", "selling to companies", "enterprise marketing", "we sell to businesses", "B2B brand strategy", "thought leadership strategy", "B2B content marketing", "account-based marketing brand", "B2B positioning", "how do we build trust with buyers", or is marketing a product or service sold to other businesses rather than consumers.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks about Vibe Motion, motion graphics, kinetic typography, animated text, brand animations, logo animations, infographic animation, presentation animation, data-driven video, or prompt-to-motion-graphic workflows. Vibe Motion is fundamentally different from video generation — it creates deterministic code-based motion graphics, not AI-predicted pixel sequences. Use this when the text/logo must stay perfectly crisp and editable (code). For a cinematic/kinetic AI-generated video ad built from a storyboard (pixel render, native audio), use higgsfield-motion-design instead.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to generate a cinematic still image on Higgsfield, asks about shot framing, camera angle, or composition for image prompts, needs a specific shot type (close-up, wide shot, cowboy shot, etc.), or is working with [img] reference-based image generation. Covers distance & size shots, camera angles, and camera movement keywords optimized for AI image models (Soul 2.0, Nano Banana, Seedream, GPT Image, Flux, etc.).

日本語の概要は準備中です。原文の説明を表示しています。

Designs products around price using the 9 rules from Ramanujam and Tacke - WTP conversations, needs-based segmentation, Good/Better/Best configuration, monetization models, behavioral pricing, and price integrity. Use when designing new products, validating pricing for SaaS/B2B/B2C launches, choosing between subscription/usage/freemium models, fixing post-launch sales below plan, diagnosing failed launches as Feature Shock/Minivation/Hidden Gem/Undead, or when product teams say 'let's price it later'. Not for pure commodities or cost-plus regulated environments.

日本語の概要は準備中です。原文の説明を表示しています。

Dispatch to the right problem-solving technique based on how you're stuck

日本語の概要は準備中です。原文の説明を表示しています。

Replace arbitrary timeouts with condition polling for reliable async tests

日本語の概要は準備中です。原文の説明を表示しています。

First-tier tech company P9 capability advisor for evaluating, coaching, and giving career advice against a P9 senior expert, director, or business/organization-level leader profile. Use when the user asks for P9-level assessment, promotion readiness, executive capability gaps, strategic project review, resume positioning, interview preparation, or growth advice based on first-tier tech company P9 expectations.

日本語の概要は準備中です。原文の説明を表示しています。

First-tier tech company P7 capability advisor for evaluating, coaching, and giving career advice against a P7 technical/product/expert profile. Use when the user asks for P7-level assessment, promotion readiness, capability gaps, resume/project review, interview preparation, or concrete growth advice based on first-tier tech company P7 expectations.

日本語の概要は準備中です。原文の説明を表示しています。

First-tier tech company P8 capability advisor for evaluating, coaching, and giving career advice against a P8 senior expert, architect, or domain-owner profile. Use when the user asks for P8-level assessment, promotion readiness, capability gaps, project or resume review, interview preparation, or growth advice based on first-tier tech company P8 expectations.

日本語の概要は準備中です。原文の説明を表示しています。

Use for authorized reverse engineering of browser extensions (Chrome/Firefox) including manifest analysis, background workers, and extension-based credential or traffic logic recovery.

日本語の概要は準備中です。原文の説明を表示しています。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.

日本語の概要は準備中です。原文の説明を表示しています。